Operational Life Research Articles

Thermal studies on cryocooler thermal masses from 4 K to 300 K for MRI applications

AbstractGifford–McMahon (GM) cryocoolers are pivotal for maintaining the temperature of MRI magnets, necessitating regular servicing for optimal performance and longevity. This study explores the geometric dimensions and shapes of superconducting magnets utilized in MRI for system cooling. The investigation demonstrates that warm-up time is contingent on heat capacity rather than geometric shapes. As a result, the design of magnets can be customized to specific shapes and sizes in accordance with favorable conditions, given that warm-up time is solely dependent on heat capacity. The primary focus is to deliberately prolong the warm-up time of the magnet relative to the GM cryocooler, consequently minimizing service intervals. Laboratory evaluations explore the use of thermal masses equivalent to MRI magnets, employing typical materials such as copper and aluminum. These masses are cooled to 4 K and then subjected to different heating powers to evaluate warm-up characteristics. Various configurations and shapes of thermal masses are numerically studied for warm-up analysis. Comparative assessments between experimental results and simulations reveal that, for cylindrical thermal masses, 80 W heating power facilitates a 76% reduction in warm-up time compared to 20 W heating across all cases. In the exploration of different geometric thermal masses, aluminum demonstrates a remarkable 35% decrease in warm-up time compared to copper. A noteworthy finding emerges, indicating that warm-up time is contingent on heat capacity rather than geometric shapes. These insights hold substantial relevance, particularly in systems with large thermal capacities, such as superconducting magnets. The study contributes valuable knowledge to the optimization of GM cryocoolers for enhanced MRI magnet performance and extended operational life.

Investigation of burnout effect in turbine blade tip leakage at transonic conditions – a numerical study

Abstract In the aviation industry, turbine blade tip leakage significantly impacts the economy due to aerodynamic losses in the turbine. The tip leakage flow increases when the tip surface is exposed to high heat loads from the burnout effect, contributing to nearly 30% of the total loss in the turbine stage. This study numerically investigates two-dimensional flat tip and burnt-out tip models under different flow accelerations at transonic conditions. Variations in the discharge coefficient are examined for different pressure ratios across the tip gap. Flow and shockwave patterns for various blade tip geometries are obtained and analyzed. The burnt-out tip notably increases tip leakage, and a significant decrease in turbine efficiency is observed beyond a critical burnout limit. The quantified losses at different stages of blade tip burnout are used to predict the effective operational life of the blade. A correlation is developed to relate the non-dimensional tip-leakage flow parameters to the normalized blade-tip geometry.

Damage Diagnostics of Miter Gates Using Domain Adaptation and Normalizing Flow-Based Likelihood-Free Inference

Miter gates are vital civil infrastructure components in inland waterway transportation networks. To provide risk-informed insights for decisions related to repair and maintenance, sensors have been installed on some miter gates for monitoring. Despite the monitoring system's ability in collecting a large volume of monitoring data, accurately diagnosing damage state in such large structures remains challenging due to the lack of labeled monitoring data, since these structures are designed with high reliability and for a long operation life. This paper addresses this challenge by proposing a damage diagnostics approach for miter gates based on domain adaptation. The proposed approach consists of two main modules. In the first module, Cycle-Consistent generative adversarial network (CycleGAN) is employed to map monitoring data of a miter gate of interest and other similar yet different miter gates into the same analysis domain. Subsequently, a normalizing flow-based likelihood-free inference model is constructed within this common domain using data from source miter gates whose damage states are labeled from historical inspections. The trained normalizing flow model is then used to predict the damage state of the target miter gate based on the translated monitoring data. A case study is presented to demonstrate the effectiveness of the proposed method. The results indicate that the proposed method in general can accurately estimate the damage state of the target miter gate in the presence of uncertainty.

Life Cycle Prediction of Airport Operation Based on System Dynamics

Traditional airport development planning often overlooks an in-depth consideration of the airport operation life cycle, which frequently causes deviations from planned objectives during operation. This paper presents a framework for predicting and segmenting the airport operation life cycle by integrating the dynamic characteristics of the System Dynamics (SD) model with the static properties of Logistic modeling to examine the development trajectory of airport operations. The influencing factors in this model are selected across three levels: airport, city, and macro-environment. A system dynamics model of airport operation is constructed using causal loop diagrams and system flow diagrams. Using Guangzhou Baiyun International Airport (CAN) as a case study, the airport’s operational capacity from 2005 to 2035 is predicted through SD simulation. Subsequently, the airport operation life cycle from 2005 to 2050 is forecasted and segmented using Logistic modeling. The results indicate that, under the standard scenario, CAN’s operational capacity experiences two declines in 2016 and 2020, attributed to airport construction and emergencies. Logistic modeling identifies three distinct life cycle phases in the airport’s operation. Furthermore, by comparing various airport operation scenarios, the analysis reveals that fluctuations in the city economy significantly impact the airport’s operational system without altering its overall development trajectory. In contrast, the occurrence of emergencies can substantially modify the airport operation life cycle.

Recognition of Impact Load on Connecting-Shaft Rotor System Based on Motor Current Signal Analysis.

Impact loads affect the operational performance and safety life of rolling equipment's connecting-shaft rotor system, even causing faults and accidents. Therefore, recognizing and investigating impact loads is of great significance. Hence, a load recognition method based on motor current information is proposed in this paper to recognize impact loads on the connecting-shaft rotor system. First, the fast Fourier transform is used to obtain the frequency domain information for the motor's current response signal from the rotor system load recognition test. Consequently, the required load response information can be presented more clearly using the singular value decomposition method to remove the power frequency components in the current signal. Then, wavelet packet decomposition is performed on the signal to generate energy analysis feature vectors. A qualitative recognition of the impact load on the system is achieved by learning vector quantization neural networks; the resulting load recognition results are good. These findings indicate that using the motor current as the analysis signal can solve the problem of the difficult layout for traditional vibration sensors in rolling sites. The preprocessing and recognition method of the current response signal can recognize the impact load, confirming the applicability and feasibility of the proposed method.

Implementation of Fuzzy Logic Scheme for Assessment of Power Transformer Oil Deterioration Using Imprecise Information

This research aims to analyze the implementation of a fuzzy logic-based approach in improving the diagnosis of power transformer oil deterioration, which is critical for maintaining the efficient performance and operational life of transformers. Traditional diagnoses are based on strict measurements that do not account for the factors of variability and uncertainty of the actual data. In this article, we perform six different types of tests in this regard, and data have been collected during the period of 2021 to 2022 of 188 power transformer failures in the New KotLakhpat Lahore unit, whose voltage range is 132/66 kv and rating capacity is 40/50 MVA. In this case, a fuzzy logic-based scheme is developed based upon the membership function, a rule-based and defuzzification method that works with imprecision and the implementation of uncertainty in assessing the condition of transformer oils. Moisture, acidity, and a dissolved gas analysis indicator, along with other indication approaches such as interfacial tension, viscosity, and tangent delta measurement, are used to analyze the deterioration process in transformer oils. In the visual representation, oil samples with the following properties were first fuzzified: 19.9 mm2/s of viscosity, 0.453 mgKOH/g of acidity, 695 ppm of DGA, 20.8 mg/kg of moisture, 19.98 of IFT, and 4.35 × 100.14 of tangent delta. The output that was generated by software using the values entered into the parameters (HI and Age) after defuzzification is 45. Fuzzy logic serves as a concrete framework for transforming the diagnostics system and deterring the threats to the entire transformer’s health and reliability in the future. By using this technique, various faults were hypothetically and practically analyzed in a transformer to implement early detection technologies with the possibility to reduce maintenance costs and extend operational life up to 45 years. Various case studies indicate the effectiveness of fuzzy logic in comparison to traditional diagnostics.

Improving the operational life and reliability of the machine and tractor fleet by non-selective methods of tribotechnics

The fl eet of domestic tractors and combines has signifi cantly used up its operational life, has a reduced time to failure, frequent repairs and high operating costs: up to 50 billion rubles per year. The engineering service of agricultural enterprises has signifi cantly weakened, most of the maintenance work on domestic machines is carried out by the owners of the machinery themselves, which causes their low quality and frequent failures. In this regard, new methods and means are being developed to improve the reliability and service life of machines, which will also affect imported equipment.

Was the abolition of the Aboriginal and Torres Strait Islander Commission an act of dispossession?

AbstractThe Aboriginal and Torres Strait Islander Commission (ATSIC) has been described as one of the most comprehensive regional and national governance structures for Indigenous people in Australia. This paper looks briefly at its operational life between 1990 and 2005 and focusses on its abolition, arguing that this was an act of dispossession. The ATSIC was, for its time, a remarkable achievement for both the nation state and Indigenous people. Acting as an institution to both represent and deliver services to Indigenous people, the ATSIC model was, and could have remained, a powerful organisation for enacting critical change. Constructed and then removed by the nation state, the ATSIC's abolition dispossessed Indigenous people of a political framework dedicated to organising an Indigenous collective voice. This dispossession, different from earlier waves of dispossession from land, resources and cultural freedoms, can be understood by the application of critical Indigenous institutional analysis. Through its own structure and electoral representation, the ATSIC had made visible the quest for self‐determination and gave Indigenous people decision‐making powers not since replicated. Redirecting ATSIC's limited decision making back to government exposed the illusion of control. The ATSIC's abolition left a void in the growing capability of Indigenous people to self‐determine and a gaping hole in Australia's national political imagination.

Failure analysis of ternary lithium-ion batteries throughout the entire life cycling at high temperature

The operation life is a key factor affecting the cost and application of lithium-ion batteries. This article investigates the changes in discharge capacity, median voltage, and full charge DC internal resistance of the 25Ah ternary (LiNi0.5Mn0.3Co0.2O2/graphite) lithium-ion battery during full life cycles at 45 °C and 2000 cycles at 25 °C for comparison. The batteries before and after cycling were disassembled, and the structure, morphology, interface characteristics, element content of the cathode and anode plates of the battery were characterized. By analyzing the failure factors of the performance of the ternary batteries during the 45 °C cycling, a reaction mechanism for the rapid decline of high-temperature cycling performance of ternary batteries has been proposed. The results show that the performance degradation of the ternary lithium-ion batteries in the whole life operated at high temperature is characterized by slow decline in the initial stage and rapid drop in the latter stage. Further analysis of physical and chemical performance revealed irreversible damage to both the cathode and anode. The dissolution of transition metal ions from the cathode and their deposition on the anode surface catalyze the decomposition of electrolyte solvents to produce a large amount of gas. Gassing, accompanied by the deposition of Li2CO3 and the thickening of SEI, leads to an increase in the internal resistance of the battery. The coupling between gassing and increased internal resistance is responsible for the rapid drop in the performance of the ternary batteries during high-temperature cycling.

Performance of 3D trench silicon pixel sensors irradiated up to [formula omitted]

Tracking particles at extreme fluences requires the accurate measurement of the charged particle timing at the pixel level in order to cope with the increased occupancy of HL-LHC experiments. Maintaining this precision throughout the operational life of the detector is crucial. This work demonstrates that the 55×55μm2 wide 150μm thick 3D trench-type pixels, developed by the TimeSPOT Collaboration, maintain the performance of non-irradiated sensors even after exposure to fluences as high as 1⋅10171MeVneqcm−2. The preliminary results of a beam test characterization using minimum ionizing particles at the SPS North area beam facility reveal that the charge collection and the time resolution of the irradiated sensors are comparable to those of non-irradiated ones, by increasing the operational bias voltage. A minor reduction in detection efficiency, approximately 4%, is observed post-irradiation. Currently, 3D trench-type pixels are among the fastest pixel detectors available for tracking charged particles and hold significant promise for future tracking system upgrades. This preliminary evaluation suggests their suitability for use in even harsher radiation environments than High Luminosity Large Hadron Collider (HL-LHC) such as future experiments at the Future Circular Hadron Collider (FCC-hh).

Magneto-acousto-electrical tomography based on frequency response compensated linearly frequency-modulated signal stimulation

Objective. In magneto-acousto-electrical tomography (MAET), linearly frequency-modulated (LFM) signal stimulation uses much lower peak voltage than the spike pulse stimulation, lengthening the operation life of the transducer. However, due to the uneven frequency responses of the transducer, the low-noise amplifier (LNA), and the bandpass filter (BPF), MAET using LFM signal stimulation suffers from longitudinal resolution loss. In this paper, frequency response compensated linearly frequency-modulated (FRC-LFM) signal stimulation is investigated to resolve the problem.Approach. The physical model of measurement of the frequency responses of the transducer and the cascading module of the detection electrodes, the LNA, and the BPF is constructed. The frequency responses are approximated by fitting a curve to the measurement data. The frequency response compensation function is set to the reciprocal of the product of the frequency responses. The digital FRC-LFM signal is generated in MATLAB and converted to analog signal through an arbitrary waveform generator. Two groups of MAET experiments are designed to confirm the performance of the FRC-LFM signal stimulation. Pure agar phantom with rectangular through-holes and agar phantom with pork tissue inclusion serve as the samples.Main results. The pulse-compressed magneto-acousto-electrical signal obtained using FRC-LFM stimulation has narrower main-lobe than that obtained using LFM excitation, although the signal to noise pulse interference ratio of the former is little lower than that of the latter, which is due to the limitation of the power amplifier. FRC-LFM also proves to be an effective method to utilize the frequency outside the working band of the transducer in MAET.Significance. The method in this study compensates for the longitudinal resolution loss due to the uneven frequency responses. Combining with high-capability power amplifier and high-performance LNA, the MAET using FRC-LFM signal stimulation can potentially achieve high longitudinal resolution and high sensitivity, advancing MAET toward the clinical application.

Numerical simulation of multiphase flow and prediction of sediment wear in a large Pelton turbine

AbstractThe problem of sediment wear presents a significant challenge for hydraulic turbines operating in sediment‐rich rivers, particularly for high‐head Pelton turbines. In this study, the VOF model, SST k–ω model, and DPM model were employed to simulate the gas–liquid–solid three‐phase flow within a large Pelton turbine, which operates under a rated water head of 671 m and has a single capacity of 500 MW, at a hydropower station situated on a sediment‐laden river. The sediment wear prediction model, derived from the sediment wear test of the model turbine, was utilized to forecast the sediment wear on the flow components of the Pelton turbine at the hydropower station. The results show that there are obvious pressure and velocity gradients near the nozzle outlet of the Pelton turbine in the power station, and the wear of the nozzle surface is gradually increasing, and the wear in the downstream area of the nozzle is more serious. The wear rate at the needle tip surface reached 1.372 μm/h, while the socket ring surface exhibited a wear rate of 3.175 μm/h. he highest wear rate recorded for the water bucket is 0.940 μm/h. After a year of continuous operation, the maximum erosion observed was 5.62 mm on the runner bucket made of stainless steel and wear‐resistant metal, 8.23 mm on the spray needle, and 19.05 mm on the nozzle mouth ring, highlighting the severity of sediment wear on the Pelton turbine. It is recommended that surface treatment technology be applied to the flow‐through components of the Pelton turbine at this hydropower station to enhance the wear resistance of the turbine and extend the operational life of the unit.

Cost-effective reliability level in 100% renewables-based standalone microgrids considering investment and expected energy not served costs

Loss of load probability (LOLP) and expected energy not served (EENS) are commonly used in electrical power systems to evaluate reliability. LOLP defined as the probability that available generation capacity will be inadequate to supply customer demand. EENS defined as the expected amount of energy not being served to consumers by the system during the period considered due to system capacity shortages or unexpected power outages. Loss of Load Frequency (LOLF) is referred to a number of loss of load (LOL) event happened in the operation life span of the SMG. Loss of Load Reduction (LOLR) is defined as the required reduction in LOLF to obtain a specific reliability level. While power systems are designed to minimize LOLP and EENS, this is constrained by the total cost: investment cost, operation and maintenance cost, and cost of customer interruption (CCI). This research considers Standalone Microgrid (SMG), also known as Autonomous Microgrid which only operates in off-grid mode and cannot be connected to wider electrical power system. When designing a 100 % renewable energy integrated SMGs, it is crucial to determine the cost-effective reliability level (CERL). The CERL occurs when the total cost is minimum. This research proposes an approach to calculate the CERL for a fully renewable SMG. An analytical formulation is proposed to represent the LOLR needed to obtain a specific reliability level as a function of the required size of reliability improvement alternatives. The CCI is evaluated using LOLF and EENS indices. Finally, the total cost of the SMG system is evaluated for each reliability level. Consequently, the total cost of the SMG system is expressed as a function of reliability levels, and the minimum value of total cost and the corresponding reliability level are evaluated. In this research, a Monte Carlo Simulation (MCS) approach is used to find hourly LOLF, considering 25 years (219,000 h) of SMG lifespan, regression analysis is used for an analytical formulation, and mixed integer linear programming (MILP) is used for the investment decision making based on a cost minimisation approach. The result demonstrates that the CERL of the SMG system evaluated in the case study is 98.71 %.

Multi-energy harvesting: Integrating contact-mode and slide-mode triboelectric nanogenerators, and solar technologies for efficient power generation in small electronic

Harvesting energy from the environment is getting more attention daily to drive small electronics. This paper presents a hybrid energy harvesting module that uses contact-mode triboelectric nanogenerator, slide-mode nanogenerator, and solar energy to generate electrical power. The fabricated module has three parts, i.e., the base part operating in triboelectric contact mode, the rotary part employing lateral sliding triboelectricity, and solar cells for harnessing sunlight. The 3D designed module parts have been fabricated using 3D printer and laser cutting machine. Subsequently, the parts were assembled by applying triboelectric (Aluminum and Kapton) material onto them. The triboelectric contact mode generated 0.57 µW of electric power achieving power density achieved 57 µWm−2 at the contact area of 100 cm2. Electric power delivered by triboelectrification of the rotary part was 117 µW, whereas the power density was recorded as 232.6 µWm−2 at the contact area 503.36 cm2, and power delivered by solar cells was 66.64 mW. The designed module successfully delivered power to small electronic devices such as electronic thermometers, digital calculators, digital clocks, and 25 green-coloured LEDs. The implications of these findings suggest that such a hybrid module can significantly extend the operational life and independence of small-scale electronics, making it a promising solution for remote sensing, wearable technology, and IoT devices.

Optimum feature selection for classification of PD signals produced by multiple insulation defects in electric motors

Partial discharges (PD) are initiated in electrical equipment during various points of the equipment’s lifecycle. The intensity of PD defects rises continuously with time, which can lead to insulation degradation and reduced operational life of the electrical equipment. The optimum feature selection of PD signals captured, from different insulation defects, can enhance the classification accuracy of PD defects and facilitate better visualization of PD parameters for electric motor (EM) insulation monitoring and diagnostics. This paper presents a hybrid approach, based on Maximize Relevancy and Minimize Redundancy (mRMR) and random forest (RF), for the optimum feature selection and classification of PD signals in EMs containing multiple defects. For this purpose, four PD defects are developed in the EMs insulation under laboratory conditions, and 800 PD signals are acquired using a conventional IEC-60,270 experimental platform. The severity of these defects is determined and investigated based on PD characteristic parameters. Several features of both PD sweep signals and conventional PD pulses are extracted. Consequently, the mRMR feature selection technique is implemented to select the significant features of the detected PD signals. To establish the plausibility of this technique, several other feature selection algorithms, including RefliefF, Gini Index (GI), and Information Gain (IG), are introduced for the same datasets. The performance of all these feature selection algorithms is validated using three commonly used classification techniques such as RF, support vector machines (SVM), and k-nearest neighbors (k-NN). In summary, the results show that the combination of mRMR and RF proves to be the most effective feature selection algorithm for the classification of insulation defects in EMs, achieving an accuracy of 99.875%. This accuracy is significantly better than other feature selection and classification techniques and indicates its potential for application to other power system components.

Design of Gearings from Involute-Bevel Gears

The article presents formulas for determining the dimensions of involute-bevel gears and the gearings composed of them. It examines the most general cases of gearings formation, consisting of two involute-bevel gears with crossing axes (hyperboloid gearings), with intersecting axes (bevel gearings), and with parallel axes (cylindrical gearings). Gearings composed of involute-bevel gears have design, technological, and operational advantages compared to gearings composed of conventional cylindrical and bevel gears. The use of involute-bevel gearings with crossing axes allows for achieving the required contact character of the teeth from localized contact to linear contact, reducing sensitivity to manufacturing and assembly errors, and increasing the load capacity of the gearing compared to helical gearings from cylindrical gears. Bevel gearings with involute-bevel gears allow for the creation of gearings with any desired small shaft angles, which is difficult to achieve with conventional bevel gears. The use of internal meshing bevel gearings with modified tooth profiles in planetary reducers allows for gearings comparable to harmonic drives in terms of power and kinematic characteristics, but with a higher operational life. The use of involute-bevel gears in cylindrical gearings improves the smoothness of the mechanism and allows for adjusting the center distance and backlash in the meshing, making them suitable for backlash-free drives. By combining the taper angles of the gears and the inclination of the teeth, it is possible to create a one-way rotation mechanism - a freewheel mechanism. Modern CAD systems do not take into account the geometry features of gearings composed of involute-bevel gears, which limits their application in technology. The article proposes an algorithm for calculating the main geometric parameters of gearings composed of involute-bevel gears with arbitrary axis placement in space. Examples of geometric calculations of various types of gearings based on the proposed algorithm are provided.

Energy Harvesting Deadline Monotonic Approach for Real-time Energy Autonomous Systems

This paper presents an innovative scheduling algorithm designed specifically for real-time energy harvesting systems, with a primary focus on minimizing energy consumption and extending the battery's lifespan. The algorithm employs a fixed priority assignment which is the deadline monotonic policy, we have chosen it for its optimality and superior performance compared to other fixed priority scheduling methods. To achieve a balance between energy efficiency and system performance, we incorporated a DVFS (Dynamic Voltage and Frequency Scaling) technique into the algorithm. This adaptive approach enables precise control over the processor's operating frequency, effectively managing energy consumption while ensuring satisfactory system functionality. The core objective of our scheduling algorithm centers on optimizing energy utilization in real-time energy harvesting systems, specifically tailored to extend the battery's operational life. Rigorous evaluations, including comprehensive comparisons against established fixed priority scheduling algorithms, validate the algorithm's efficacy in significantly reducing energy consumption while preserving the system's overall functionality. By combining the deadline monotonic policy and DVFS technique, our proposed algorithm emerges as a promising solution for energy-autonomous systems, contributing to the advancement of sustainable energy practices in real-time applications. As energy harvesting technologies continue to progress, our algorithm holds valuable potential to provide critical insights for enhancing the efficiency and reliability of future energy harvesting systems.

Study on Oil Resistance of Polyurethane Protective Material

Abstract The polyurethane protective tape is a new type of protective material made by coating high performance pressure-sensitive adhesive on polyurethane elastomers, which is widely used in aviation. During its operational life, the polyurethane protective tape inevitably comes into contact with oil, and its oil resistance directly impacts its lifespan. This study focuses on the polyurethane protective tape and conducts immersion tests in No. 15 aviation hydraulic fluid, aircraft gear oil 4450 and RP3 aviation kerosene at room temperature. A comparative analysis was also conducted on the tensile strength, tear resistance, fracture morphology, chemical structure, and thermophysical properties before and after immersion. The research indicates that the tensile properties of polyurethane protective tapes remain essentially unchanged after immersion in RP3 aviation kerosene. After being immersed in No.15 aviation hydraulic fluid and aircraft gear oil 4450, the tensile strength of the polyurethane protective tape gradually decreases. Furthermore, compared to No.15 aviation hydraulic fluid, the rate of tensile strength reduction in polyurethane protective tape immersed in aircraft gear oil 4450 is more rapid. The resistance to tearing of polyurethane protective tapes diminishes gradually with prolonged immersion, with the rate of decline being greater for aircraft gear oil 4450 than for No.15 aviation hydraulic fluid, and even greater for RP3 aviation kerosene. The decrease in mechanical properties of polyurethane protective tapes after immersion in oil is attributed to the swelling effect of the oil, which reduces the intermolecular forces within the polyurethane material and leads to a decrease in physical cross-linking. This process is physical aging, with no evident chemical aging occurring.

Exploring the effect of Ti doping on the friction characteristic of DLC films on the surface of pump plunger in petroleum extraction environments

DLC film is considered to be one of the most promising film materials for improving the abrasion resistance and operation life of pump plungers draw upon its low friction and high hardness, but the friction characteristics and mechanism of the doping element Ti on pump plungers under the petroleum extraction environment are still unclear. In this paper, the friction performance and mechanism of the doping Ti for DLC film on the appearance of the pump plunger under the petroleum extraction environment were investigated at the microscopic scale by using the reactive molecular dynamics. The outcome shows that the Ti-DLC displays a reduction in average friction force of 78.82 % and a decrease in average temperature of 40.33 % in the oil extraction environment, thus improving the abrasion resistance of the pump plunger. Moreover, with the increase of Ti content, the friction will gradually decrease, and significantly low friction behavior can be even materialized without lubrication. It is found that the main reason for the low friction of Ti-DLC film is that the layered structure determined by Ti concentration is formed on the appearance of friction pair, which inhibits the formation of interfacial carbon bond and reduces the shear stress on the contact surface.

In situ microbubble-mediated strategy for highly efficient anti-crude oil-fouling membrane with parallel nanosheet structure

Membrane fouling caused by highly viscous oils severely hampers the long-term application of oil–water separation membranes. In situ aeration, achieved by applying a voltage to the membrane to produce bubbles, can effectively reduce the adhesion of oil contaminants. Herein, the parallel NiFe-layered double hydroxide arrays were successfully constructed on Ni foam using a hydrothermal method. Compared with NF@NFLDH having randomly aligned nanosheet arrays, NF@NFLDH-P can produce more numerous micro-size bubbles. A substantial number of the microbubbles spontaneously coalesced with oil droplets, and the synergy of buoyancy and kinetic energy significantly hindered oil fouling on the NF@NFLDH-P membrane. Specifically, this microbubble–mediated anti-oil-fouling strategy substantially reduced the flux attenuation and maintained a high flux recovery ratio during long-term crude oil–water separation, exhibiting a great operational life. This study suggests an innovative way to design future anti-fouling membranes with bubble-mediated capabilities.